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Activity Number:
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243
- Brain Structural and Functional Connectivity Analysis
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Type:
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Contributed
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Date/Time:
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Monday, July 30, 2018 : 2:00 PM to 3:50 PM
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Sponsor:
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Section on Statistics in Imaging
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Abstract #329012
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Title:
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Comparison of Functional Brain Networks via Correlation Preserving Random Networks
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Author(s):
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Ixavier Higgins* and Suprateek Kundu and Ying Guo
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Companies:
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Rollins School of Public Health-Emory University and Emory University Rollins School of Public Health and Emory University
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Keywords:
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Brain Network ;
Functional Connectivity;
Network Comparison
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Abstract:
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Network analysis is a popular approach for characterizing the brain's organizing principles. Irregular communication between brain regions in diseased populations contributes to abnormal network topology when compared to healthy brains. To identify these neural dysfunctions, we propose a differential degree test (DDT) which finds brain regions incident to a significant number of differentially weighted edges (DWEs). We achieve this by generating an appropriate set of null networks which are matched on the first and second moments of the observed difference network using the Hirschberger-Qi-Steuer (HQS) algorithm. This formulation permits separation of the network's true topology from that induced by the correlation measure. Nuisance topology introduced by the correlation measure is typically ignored but can drive interregional connectivity in ways unrelated to brain function. Extensive numerical studies and application to a Major Depressive Disorder data set reveal the advantages of our proposed method.
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Authors who are presenting talks have a * after their name.
